Potential Sand and Gravel Resources of the Canton 30 x 60-Minute Quadrangle, Ohio

The Ohio Department of Natural Resources (ODNR), Division of Geological Survey has completed a reconnaissance map showing areas of mineable sand and gravel resources in the Canton, Ohio, 30 x 60-minute 1:100,000-scale quadrangle. The main purpose of this map was to create a reconnaissance-level map that would show the potential for mining sand-and-gravel in this quadrangle. The map shows areas of surficial materials in increments of 10 feet and then differentiates sand, sand and gravel, and ice-contact deposits from finer grained materials, such as glacial till, lacustrine clay and silt, and alluvial materials. The sand and sand-and-gravel units include both surficial and buried outwash and valley train deposits and ice-contact deposits, such as kames, kame terraces, and eskers. This map was created to show the total thickness or accumulation of sand and gravel in the Canton 30 x 60-minute quadrangle. The thickness of sand-and-gravel deposits helps determine if it is economically viable.United States Geological Survey: National Cooperative Geologic Mapping Program, Great Lakes Geologic Mapping Coalitio

Suitablility for Solid-Waste Disposal in the Lorain 30 x 60-Minute Quadrangle

The Ohio Department of Natural Resources (ODNR), Division of Geological Survey has completed a reconnaissance map showing areas suitable for solid waste disposal in the Lorain, Ohio, 30 x 50-minute (1:1,100,000-scale) quadrangle. The main purpose of this map is to provide a reconnaissance level map that shows the relative suitability of various surficial materials for the disposal or containment of solid waste in this quadrangle. Our goal was to create this map from existing ODNR Division of Geological Survey maps and GIS datasets as much as possible. Consequently, the Lorain map is a derivative map based directly from the ODNR Division of Geological Survey SG-2 Series map, Surficial Geology of the Lorain and Put-in-Bay 30 x 60 Minute Quadrangles (Pavey and others, 2005). The SG-2 series features maps based upon polygons that represent a “stack” of mapped unit lithologies and thicknesses. These maps show surficial materials in increments of 10 feet within each polygon across the study area. A set of queries were run in ESRI ArcGIS to determine the range of thickness and nature of the sediments. The main premise of this map is to specify areas of thick, fine-grained glacial till and glaciolacustrine silt and clay deposits for solid-waste disposal and containment. A minimum of 30 feet of fine-grained material was deemed necessary for waste disposal for areas where the drift overlies shale; siltstone; or interbedded, shaley limestone. If the fine-grained material was directly overlying an aquifer, the minimum required thickness was increased to 50 feet. Aquifers included sand and gravel, sandstone, limestone, and dolomite. Areas with over 20 feet of sand and gravel or sand at the surface (e.g., kames, beach ridges) were excluded as were areas with alluvium (active streams) and organic deposits at the land surface. The main factor in the decision-making process was to have adequate fine-grained materials overlying the aquifers.United States Geological Survey, National Cooperative Geologic Mapping Program, Great Lakes Geologic Mapping Coalitio

Lawson criterion for ignition exceeded in an inertial fusion experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion

Karst of the Belfast and Sugar Tree Ridge 7.5-Minute Quadrangles, Ohio

Chiefly maps.; "This project was funded by the Great Lakes Geologic Mapping Coalition surficial mapping grant program"--Page iv.; Includes bibliographical references (page 6).; "A digital elevation model (DEM), generated from LiDAR data, was used to create a map layer that identified low, enclosed areas. To locate potential sinkholes, these low spots were cross referenced with known karst points from previous studies, bedrock geology, aerial photography of multiple sources and ages, soil maps, glacial drift thickness maps, and water well logs. ... Suspected karst features were then visited in the field, evaluated, and photographed. Through this process some of the LiDAR-derived depressions were found not to be sinkholes; features such as building foundations, broken field tiles, steep-walled streams, road culverts, and glacial features often produced enclosed areas similar in shape to sinkholes. Springs do not typically show up as depressions unless a catch basin was built and subsequently failed, thus many were located during field work by spotting springhouses. Field visits are important for confirming sinkhole sizes and depths as well. ..."--Page 2.; Harvested from the web on 12/22/1

Karst of the Western Delaware County, Ohio, Region

Includes bibliographical references.; "To locate sinkholes, LiDAR was used to create a map layer that identified low, enclosed areas. These low spots were cross referenced with know karst points, bedrock geology, aerial photography of multiple sources and ages, soil maps, drift thickness, and water well logs to locate potential sinkholes. Suspect locations then were visited in the field, evaluated, and photographed. Through this process we quickly learned that many of the LiDAR returns were not sinkholes; features such as building foundations, broken field tile, steep-walled streams, and road culverts often produced enclosed areas similar in shape to sinkholes. Many of these features were eliminated using 6-inches-per pixel aerial photography and experience from field verification. The resulting map ... can be used to monitor the growth of preexisting sinkholes and the development of new karst features. Furthermore, areas of land development should be carefully planned in regions of dense karst since they are highly susceptible to pollution and subsidence."--Page 1

Karst of Northern Portions of the Peebles and Jaybird 7.5-Minute Quadrangles, Ohio

Chiefly maps.; "GIS and cartography: Dean R. Martin; Graphic design & layout: David S. Orr; Editing: Charles R. Salmons"--Page ii.; "This project was funded by the Great Lakes Geologic Mapping Coalition surficial mapping grant program under Cooperative Agreement G17AC00219"--Page iv.; Includes bibliographical references (pages 5 and 9).; A digital elevation model (DEM), generated from Light Distance and Ranging (LiDAR) data, was used to create a map layer that identified low, enclosed areas. To locate potential sinkholes, these low spots were cross referenced with known karst points from previous studies, bedrock geology, aerial photography, soil maps, glacial drift thickness maps, and water well logs. Many depressions were removed from consideration when it was determined they were not sinkholes. Remaining depressions were then visited in the field, evaluated, and photographed. Through this process more of the LiDAR-derived depressions were found not to be sinkholes. Features such as building foundations, broken field tiles, steep-walled streams, road culverts, and glacial features often produced enclosed areas similar in shape to sinkholes. Springs do not typically do not show up as depressions, and they were located during field work by spotting springhouses. Field visits are important for confirming sinkhole dimension because LiDAR often under-reports maximum sinkhole size and depth

Karst of Springfield, Ohio

Chiefly maps.; Includes bibliographical references.; "To locate sinkholes, a digital elevation map (DEM) generated from LiDAR (Light Detection and Ranging) data was used to create a map layer that identified low, enclosed areas. To locate potential sinkholes, these low spots were cross referenced with know karst points, bedrock geology, aerial photography of multiple sources and ages, soil maps, drift thickness maps, and water well logs. Suspect locations then were then visited in the field, evaluated, and photographed. Through this process many of the LiDAR returns were found not to be sinkholes; features such as building foundations, broken field tiles, steep-walled streams, and road culverts often produced enclosed areas similar in shape to sinkholes. Many of these misleading features were eliminated remotely using 6-inches-per pixel aerial photography and experience from past field verification."--Page 1

Karst of the Fireside quadrangle and portions of the Flat Rock and Clyde quadrangles, Ohio

Chiefly maps.; Includes bibliographical references.; "A digital elevation map (DEM), generated from LiDAR (Light Detection and Ranging) data, was used to create a map layer that identified low, enclosed areas. To locate potential sinkholes, these low spots were cross referenced with known karst points, bedrock geology, aerial photography of multiple sources and ages, soil maps, glacial drift thickness maps, and water well logs. Suspect locations then were then visited in the field, evaluated, and photographed. Through this process some of the LiDAR returns were found not to be sinkholes; features such as building foundations, broken field tiles, steep-walled streams, road culverts, and glacial features often produced enclosed areas similar in shape to sinkholes. Many of these misleading features were eliminated remotely using both 6-inches-per pixel aerial photography and experience from past field verification. However, many points remained that could not be distinguished remotely and these were visited in the field."--Page 1

Karst of the Hillsboro, New market, New Vienna, and Leesburg quadrangles, Ohio

Chiefly maps.; Includes bibliographical references.; "A digital elevation map (DEM), generated from LiDAR (Light Detection and Ranging) data, was used to create a map layer that identified low, enclosed areas. To locate potential sinkholes, these low spots were cross referenced with known karst points, bedrock geology, aerial photography of multiple sources and ages, soil maps, glacial drift thickness maps, and water well logs. Suspect locations then were then visited in the field, evaluated, and photographed. Through this process some of the LiDAR returns were found not to be sinkholes; features such as building foundations, broken field tiles, steep-walled streams, road culverts, and glacial features often produced enclosed areas similar in shape to sinkholes. Many of these misleading features were eliminated remotely using both 6-inches-per pixel aerial photography and experience from past field verification. However, many points remained that could not be distinguished remotely and these were visited in the field."--Page 1